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Leeuwen and Yang (arXiv:2403.15292). As a PhD student on this project, you will: develop mathematical theory for non-linear inverse problems governed by wave equations; design and analyse numerical
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traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where possible. This innovative new approach enables more efficient and
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possible? What are the optimal laser and target properties? Project goal The goal of this joint experiment-theory project is to elucidate the properties of beyond-EUV radiating plasmas. The work will entail
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heterogeneity and typologies, diverse values and valuation of nature, and theory of transitions and transformations Conducting and analyzing semi-structured interviews and workshops with stakeholders Develop
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traffic flow theory and simulation. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your
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resources, public services, and guarantees of rights — and where they turn to repression instead. GRID combines a new cross-national dataset coding governments’ de jure and de facto responses since 1989
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, for example, Portuguese, Dutch, French, English, Spanish, and/or Danish) Prior experience with archival/paleographic research, qualitative coding, corpus-based text analysis Familiarity with intersectionality
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theory-driven research with a clear eye for practical implications and policy recommendations. A team player with strong communication skills. Excellent academic writing skills (English). Dutch language
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Our theory group is a worldwide leader in studying the statistical physics of living systems. We
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join a highly interdisciplinary project at the interface of simulations and theory of porous materials, peptide self-assembly and adaptive materials. You will have access to state of the art